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Competência em Informação como Fator de Inovação Social

2022· article· pt· W4283812275 on OpenAlexaff
Alessandra de Souza Santos, Luiz Cláudio Gomes Maia, Marta Macedo Kerr Pinheiro

Bibliographic record

VenueBrazilian Journal of Information Science research trends · 2022
Typearticle
Languagept
FieldDecision Sciences
TopicBusiness and Management Studies
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsHumanitiesSociologyPsychologyPhilosophy

Abstract

fetched live from OpenAlex

O presente artigo propõe-se a analisar a competência em informação como sendo um fator de promoção de inovação social, tendo-se em vista uma possível correlação entre as matrizes teóricas dessas duas temáticas. A inovação social visa à transformação social por meio de mudanças nas práticas sociais, satisfazendo necessidades humanas e promovendo inclusão social, com uma consequente mudança de relações de poder, uma vez que o próprio conhecimento pode ser considerado inovação social. A competência em informação é considerada base para a aprendizagem ao longo da vida pois se trata de uma meta-competência capaz de auxiliar o indivíduo a lidar com necessidades informacionais e a compreender, criar e utilizar criticamente a informação nos mais variados contextos. O presente trabalho tem por objetivo delinear o alinhamento dos temas inovação social e competência em informação, realizando uma análise sobre como a perspectiva transformacional de estudos primários realizados na literatura sobre competência em informação pode ser correlacionada à inovação social em uma perspectiva de inclusão e emancipação sociais.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.039
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.008
Science and technology studies0.0070.022
Scholarly communication0.0210.019
Open science0.0020.011
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0200.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.171
GPT teacher head0.464
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2022
Admission routes1
Has abstractyes

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